R: Forms expected (co)variances for GLMMs fitted with MCMCglmm

buildV {MCMCglmm} | R Documentation

## Forms expected (co)variances for GLMMs fitted with MCMCglmm

### Description

Forms the expected covariance structure of link-scale observations for GLMMs fitted with MCMCglmm

### Usage

    buildV(object, marginal=object$Random$formula, diag=TRUE, it=NULL, posterior="mean", ...)

### Arguments

`object` | an object of class `"MCMCglmm"`
`marginal` | formula defining random effects to be maginalised
`diag` | logical; if `TRUE` the covariances betwween observations are not calculated
`it` | integer; optional, MCMC iteration on which covariance structure should be based
`posterior` | character; if `it` is `NULL` should the covariance structure be based on the marginal posterior means (`'mean'`) of the VCV parameters, or the posterior modes (`'mode'`), or a random draw from the posterior with replacement (`'distribution'`). If `posterior=="all"` the posterior distribution of observation variances is returned
`...` | Further arguments to be passed

### Value

If `diag=TRUE` an n by n covariance matrix. If `diag=FALSE` and `posterior!="all"` an 1 by n matrix of variances. If `posterior=="all"` an nit by n matrix of variances (where nit is the number of saved MCMC iterations).

### Author(s)

Jarrod Hadfield j.hadfield@ed.ac.uk

### See Also

`MCMCglmm`

[Package MCMCglmm version 2.30 Index]